rss订阅数据爬取及数据处理
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@@ -23,11 +23,31 @@ class IntelligenceSystem:
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self._setup_signal_handlers()
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self._setup_signal_handlers()
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log.info("系统启动 - 运行在Cron调度模式")
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log.info("系统启动 - 运行在Cron调度模式")
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# 时间追踪变量
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last_status_print_time = time.time() # 上次打印状态的时间
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last_hourly_report_time = time.time() # 上次小时统计的时间
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status_print_interval = 60 # 每分钟打印一次状态（60秒）
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hourly_report_interval = 3600 # 每小时统计一次（3600秒）
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try:
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try:
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# 主循环 - 仅负责定期检查任务
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# 主循环 - 仅负责定期检查任务
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while self._running:
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while self._running:
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current_time = time.time()
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# 判断是否需要打印状态（每分钟一次）
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should_print_status = (current_time - last_status_print_time) >= status_print_interval
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# 检查并执行到期任务
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# 检查并执行到期任务
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self.scheduler.check_and_run_tasks()
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self.scheduler.check_and_run_tasks(print_empty_status=should_print_status)
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# 更新最后打印时间
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if should_print_status:
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last_status_print_time = current_time
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# 检查是否需要进行小时统计（每小时一次）
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if (current_time - last_hourly_report_time) >= hourly_report_interval:
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self._print_hourly_stats()
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last_hourly_report_time = current_time
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# 短间隔轮询（每10秒检查一次，保证Cron时间精度）
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# 短间隔轮询（每10秒检查一次，保证Cron时间精度）
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time.sleep(10)
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time.sleep(10)
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@@ -48,6 +68,29 @@ class IntelligenceSystem:
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log.info(f"收到关闭信号 {signum}，开始关闭系统")
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log.info(f"收到关闭信号 {signum}，开始关闭系统")
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self._running = False
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self._running = False
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def _print_hourly_stats(self):
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"""打印并重置小时统计信息"""
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stats = self.scheduler.get_and_reset_hourly_stats()
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now = datetime.now().strftime('%Y-%m-%d %H:%M:%S')
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print(f"\n{'='*60}")
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print(f"📊 小时任务统计报告 - {now}")
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print(f"{'='*60}")
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print(f" 总任务数: {stats['总数']}")
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print(f" 成功: {stats['成功']}")
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print(f" 失败: {stats['失败']}")
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if stats['总数'] > 0:
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success_rate = (stats['成功'] / stats['总数']) * 100
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print(f" 成功率: {success_rate:.1f}%")
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print(f"{'='*60}\n")
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log.info(
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"小时任务统计",
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总任务数=stats['总数'],
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成功=stats['成功'],
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失败=stats['失败']
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)
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def shutdown(self):
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def shutdown(self):
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"""优雅关闭系统"""
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"""优雅关闭系统"""
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log.info("开始优雅关闭系统")
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log.info("开始优雅关闭系统")
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@@ -3,62 +3,57 @@
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### 参考文档
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### 参考文档
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https://alidocs.dingtalk.com/i/nodes/NZQYprEoWoexdo1ohPdxXvDbJ1waOeDk?utm_scene=team_space
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https://alidocs.dingtalk.com/i/nodes/NZQYprEoWoexdo1ohPdxXvDbJ1waOeDk?utm_scene=team_space
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### 程序框架
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### 程序框架（当前实现）
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```angular2html
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```angular2html
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intelligence_system/
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intelligence_system/
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├── collectors/ # 数据采集层
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├── collectors/ # 数据采集层
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│ ├── weibo_spider.py # 黑猫爬虫
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│ ├── complaint_spider.py # 投诉信息爬虫（结构化入库/附件走MinIO）
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│ ├── rss_subscriptions.py # rss订阅
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│ ├── rss_subscriptions.py # RSS 订阅抓取
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│ ├── news_api.py # 新闻接口
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│ └── internal/ # 内部数据收集（保留）
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│ │
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│ └── jian_dao_cloud.py # 简道云表单收集器（示例/占位）
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│ └── internal/ # 内部数据收集
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│ ├── jian_dao_cloud.py # 简道云表单收集器
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│
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│
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├── processors/ # 数据处理层
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├── processors/ # 数据处理层
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│ ├── data_cleaner.py # 数据清洗（去重/标准化）
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│ ├── processor_rss_data.py # RSS数据清洗、分词、过滤与入库
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│ ├── schema_mapper.py # 数据结构转换器
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│ ├── keywords.txt # 行业关键词（用于分词/过滤）
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│ ├── text_parser.py # 文本解析（PDF/HTML等）
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│ ├── stopwords.txt # 停用词
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│ ├── image_analyzer.py # 图像识别（OpenCV集成）
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│ └── ai_engine/
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│ ├── video_processor.py # 音视频分离分析
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│ └── ai_proessor_rss_data # 预留（AI分析扩展占位）
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│ │
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│ └── ai_engine/ # AI分析核心
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│ ├── nlp_processor.py # 自然语言处理引擎
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│ ├── sentiment_analyzer.py # 情感分析模型
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│ └── topic_modeler.py # LDA主题建模工具
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│
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│
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├── services/ # 应用服务层
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├── services/ # 应用服务层（保留）
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│ ├── monitoring/ # 舆情监控
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│ ├── monitoring/ # 舆情监控
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│ │ ├── opinion_monitor.py # 实时舆情追踪
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│ │ ├── opinion_monitor.py # 实时舆情追踪（占位）
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│ │ └── brand_reputation.py # 品牌口碑分析
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│ │ └── brand_reputation.py # 品牌口碑分析（占位）
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│ │
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│ ├── analysis/ # 竞品分析
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│ ├── analysis/ # 竞品分析
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│ │ ├── competitor_tracker.py # 竞品动态监控（占位）
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│ │ ├── competitor_tracker.py # 竞品动态监控
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│ │ └── swot_generator.py # SWOT分析报告（占位）
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│ │ └── swot_generator.py # SWOT分析报告
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│ ├── reporting/ # 报告服务
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│ │
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│ │ ├── daily_reporter.py # 自动化日报生成（占位）
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│ ├── reporting/ # 报告服务
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│ │ └── weekly_digest.py # 周报汇编系统（占位）
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│ │ ├── daily_reporter.py # 自动化日报生成
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│ └── alert/ # 预警服务
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│ │ └── weekly_digest.py # 周报汇编系统
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│ ├── alert_trigger.py # 动态阈值告警（占位）
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│ │
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│ └── notification_center.py # 邮件/短信通知（占位）
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│ └── alert/ # 预警服务
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│ ├── alert_trigger.py # 动态阈值告警
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│ └── notification_center.py # 邮件/短信通知
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│
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│
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├── system_management/ # 系统管理层
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├── applications/ # 应用层
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│ ├── scheduler/ # 任务调度
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│ ├── alert.py # 告警触发/通知（占位/实现中）
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│ │ └── task_scheduler.py # 任务调度器
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│ └── reporter/
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│ │
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│ ├── daily.py # 日报生成
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│ └── monitor/ # 系统监控
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│ └── monthly.py # 月报生成
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│ ├── health_monitor.py # 服务健康检测
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│ └── performance_watcher.py # 资源占用监控
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│
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│
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├── utils/ # 工具库
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├── system_management/ # 系统管理层
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│ ├── file_handler.py # 通用文件操作
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│ ├── scheduler/
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│ ├── logger.py # 日志系统
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│ │ ├── task_scheduler.py # 任务调度器（Cron表达式 + 线程池）
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│ ├── mysql_agent.py # MySQL读写管理器
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│ │ └── task_management.py # 任务管理辅助
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│ └── datetime_parser.py # 时间格式处理
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│ └── monitor/ # 系统监控（目录占位）
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│
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│
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├── config.py # 配置加载与管理
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├── utils/ # 工具库
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└── main.py # 系统入口（启动所有服务）
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│ ├── file_handler.py # 通用文件操作
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│ ├── logger.py # 跨平台日志系统（Loguru）
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│ ├── mysql_agent.py # MySQL读写管理器
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│ └── minio_agent.py # MinIO对象存储客户端
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│
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├── config.py # 配置加载与管理（含数据库/存储配置）
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├── main.py # 系统入口（Cron轮询 + 调度执行）
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└── requirements.txt # 依赖清单
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```
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```
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### 程序设计原则
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### 程序设计原则
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@@ -67,23 +62,32 @@ intelligence_system/
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3. 密钥等信息直接放在配置类中
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3. 密钥等信息直接放在配置类中
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4. 数据存储遵循"结构化存MySQL，非结构化存MinIO"原则，通过元数据关联
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4. 数据存储遵循"结构化存MySQL，非结构化存MinIO"原则，通过元数据关联
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### 主程序设计
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### 主程序与调度设计（已实现）
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主程序需要一次启动，一直运行，启动时运行一次（在代码中可取消），之后每天定时生成一次报告
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主程序以长运行进程方式启动，进入轻量轮询循环（每10秒）。调度器按Cron表达式在`main_task`表中拉取到期任务，使用线程池异步执行，并在每分钟输出运行状态、每小时汇总统计。
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主程序包含爬虫/api调度器。该调度器通过查询mysql中任务调度情况按需执行，db文件中应包含任务名称、
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- 调度器能力：
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任务路径、任务执行频率（支持按天、按周，按分钟）、上次执行时间、下次执行时间等信息
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- 基于`croniter`解析Cron表达式，支持时区（默认`Asia/Shanghai`）
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- 线程池并发执行，信号量限制最大并发（与`max_workers`一致）
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- 任务入口动态解析：支持`package.module`、`package.module.ClassName.main`、`package.module.func` 等形式
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- 成功/失败后自动计算`next_run_time`或设置15分钟后重试
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- 关键字段自动更新：`is_running`、`last_run_time`、`last_run_status`、`run_count`、`next_run_time`
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主程序应包含数据处理调度器，根据数据类别分别处理，如文本数据处理调度器、图片数据处理调度器等，
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- 主循环：
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每天定时拉取db获取到的原始数据，分别进行处理，处理完成后将结果保存到mysql中
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- 每10秒检查一次待运行任务
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- 每分钟打印当前周期统计；每小时写入累计统计日志
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- 支持`SIGINT/SIGTERM`优雅关闭，等待正在运行的任务完成
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主程序应包含日报、周报等生成，根据时间定时生成报告，报告需要存储
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### 日志设计（已实现）
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跨平台日志系统（Loguru）输出至`logs/`目录：
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### 日志设计
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- application.log：主日志，`rotation = 20MB`，达到阈值后压缩为`application.log.YYYYMMDD.zip`，`retention = 30天`
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日志系统兼容Windows、Mac、Linux平台，以`log`文件形式存储，超过20MB自动压缩。新增存储相关日志内容：
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- errors.log：错误日志（ERROR及以上），`rotation = 10MB`，`retention = 90天`
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- MySQL操作：批量插入行数、表结构变更、事务状态
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- 结构化扩展字段：日志支持`extra`键值对，自动美化并对长字段（如`sql`、`params`）截断
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- MinIO操作：文件上传/下载状态、路径、大小、耗时
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- 关联日志：MySQL记录与MinIO对象的绑定关系（如"ID:123 关联文件: collector/images/xxx.jpg"）
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建议记录的业务事件：
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- 异常日志：MySQL连接失败、MinIO上传超时、数据关联不一致等告警信息
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- MySQL读写操作要点（表名、影响行数、事务状态）
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- MinIO对象操作（对象路径、大小、耗时、状态）
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- 任务执行上下文（task_id、task_name、module_path、耗时、状态）
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### 存储系统设计（MinIO+MySQL）
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### 存储系统设计（MinIO+MySQL）
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#### 核心存储分工
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#### 核心存储分工
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@@ -113,44 +117,32 @@ intelligence_system/
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- 系统类：如任务调度表等采用功能命名（如`main_task`）
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- 系统类：如任务调度表等采用功能命名（如`main_task`）
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#### 核心表结构
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#### 核心表结构（当前落地）
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1. `collector_news_api`：新闻API采集数据表（存储新闻标题、内容等结构化数据）
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1. `main_task`：任务调度表（`task_name`、`task_type`、`module_path`、`cron_expression`、`time_zone`、`run_count`、`is_running`、`last_run_time`、`last_run_status`、`next_run_time`、`is_active` 等）
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2. `collector_complaint_spider`：投诉信息爬虫数据表（含投诉文本、附件MinIO路径`attachment_minio_path`等）
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2. `collector_rss_subscriptions`：RSS源采集数据（`文章标题`、`文章摘要`、`发布时间`、`来源URL`、`文章链接`、`是否已处理` 等）
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3. `collector_image_source`：采集层图片元数据表（存储图片URL、MinIO路径、格式、大小等）
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3. `processed_rss_data`：RSS处理结果（`分词结果`、`是否汽车相关`、`处理时间` 等）
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4. `processor_text_processor`：文本处理结果表（存储NLP分析结果、关联原文ID等）
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4. `collector_complaint_spider`：投诉信息爬虫数据（含文本与附件MinIO路径`attachment_minio_path`等）
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5. `processor_image_processor`：图片处理结果表（存储识别标签、特征向量、处理后图片MinIO路径`result_minio_path`等）
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5. 可选：`storage_object_index`（建议用于统一索引MinIO对象元数据）
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6. `storage_object_index`：MinIO对象索引表（存储所有对象的MinIO路径、哈希值、创建时间、过期时间等）
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7. `main_task`：任务调度表（存储任务名称、路径、执行频率、上次/下次执行时间等）
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8. `application_reporter_daily`：日报数据表（存储日报结构化内容、报表文件MinIO路径等）
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9. `application_reporter_monthly`：月报数据表（存储月报结构化内容、报表文件MinIO路径等）
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#### 数据交互特性
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1. **MySQL交互**
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- 支持DataFrame直接读写，提供分块处理（`chunksize`）和批量插入能力
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- 自动适配平台特性（如Windows小批次写入优化）
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- 完善的事务机制确保结构化数据一致性
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2. **MinIO交互**
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- 支持大文件分片上传、断点续传
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3. **联动机制**
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- 非结构化数据存储时，先上传至MinIO获取路径，再将路径及元数据写入MySQL
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- 读取非结构化数据时，先从MySQL获取MinIO路径，再通过路径从MinIO下载
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- 日志同步记录MySQL操作和MinIO对象操作（如"上传文件至MinIO: {path}，关联MySQL记录ID: {id}"）
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|
||||||
### 数据采集设计
|
### 数据采集设计
|
||||||
1. 结构化数据（如新闻文本、投诉内容）：直接写入对应`collector_`前缀表
|
1. 结构化数据（RSS、投诉文本）：写入`collector_`前缀表
|
||||||
2. 非结构化数据（如爬取的图片、附件）：
|
2. 非结构化数据（附件/图片等）：
|
||||||
- 调用`minio_agent.py`上传至对应存储桶
|
- 使用`utils/minio_agent.py`上传至对应存储桶
|
||||||
- 将MinIO路径、文件大小、格式等元数据写入`collector_`前缀表或`storage_object_index`表
|
- 将对象路径与元数据写入业务表或`storage_object_index`
|
||||||
3. 每个采集模块（独立py文件，`main`方法入口）需同时处理MySQL和MinIO交互，确保数据关联完整
|
3. 采集模块需同时处理MySQL与MinIO交互，确保关联完整
|
||||||
|
|
||||||
|
### 数据处理设计（RSS流程已实现）
|
||||||
|
`processors/processor_rss_data.py`流程：
|
||||||
|
- 从`collector_rss_subscriptions`加载未处理数据（可配置`limit`）
|
||||||
|
- 加载停用词与行业关键词（`stopwords.txt` / `keywords.txt`），并动态注入`jieba`词典
|
||||||
|
- 标注词性并过滤停用词，仅保留与汽车后市场相关的词汇
|
||||||
|
- 标记与过滤：出现任一行业关键词即视为相关，进入保存
|
||||||
|
- 将结果写入`processed_rss_data`，并回写源表`是否已处理 = 1`
|
||||||
|
- 输出处理统计（总量、命中量、命中率、时间）
|
||||||
|
|
||||||
### 数据处理设计
|
### 依赖与运行
|
||||||
1. 结构化数据处理：从MySQL读取原始数据，处理后写入`processor_`前缀表
|
- 依赖：见`requirements.txt`（pandas、SQLAlchemy、PyMySQL、croniter、pytz、loguru、jieba、feedparser、beautifulsoup4、minio 等）
|
||||||
2. 非结构化数据处理：
|
- 配置：在`config.py`中设置`MYSQL_CONFIG`与MinIO参数
|
||||||
- 从MySQL获取MinIO路径，通过`minio_agent.py`下载原始文件
|
- 运行：
|
||||||
- 处理后（如图片识别、视频帧提取）将结果文件上传至MinIO（处理层存储桶）
|
- 启动主程序：`python main.py`
|
||||||
- 将处理结果的结构化信息（如识别标签）和处理后文件的MinIO路径写入`processor_`前缀表
|
- 添加任务：向`main_task`插入记录，`module_path`可指向如`processors.processor_rss_data.main`
|
||||||
3. 支持多表关联存储，通过`source_id`关联原始数据与处理结果
|
|
||||||
|
|||||||
@@ -15,3 +15,4 @@ feedparser==6.0.11
|
|||||||
Markdown==3.9
|
Markdown==3.9
|
||||||
openai==1.107.3
|
openai==1.107.3
|
||||||
tqdm==4.67.1
|
tqdm==4.67.1
|
||||||
|
jieba==0.42.1
|
||||||
|
|||||||
@@ -22,6 +22,9 @@ class TaskScheduler:
|
|||||||
self.executor = ThreadPoolExecutor(max_workers=max_workers)
|
self.executor = ThreadPoolExecutor(max_workers=max_workers)
|
||||||
# 并发容量控制：限制同时运行的后台任务不超过 max_workers
|
# 并发容量控制：限制同时运行的后台任务不超过 max_workers
|
||||||
self._running_semaphore = threading.Semaphore(max_workers)
|
self._running_semaphore = threading.Semaphore(max_workers)
|
||||||
|
# 任务统计
|
||||||
|
self.hourly_stats = {'成功': 0, '失败': 0, '总数': 0}
|
||||||
|
self.hourly_stats_lock = threading.Lock()
|
||||||
log.info(f"任务调度器已初始化，最大工作线程数: {max_workers}")
|
log.info(f"任务调度器已初始化，最大工作线程数: {max_workers}")
|
||||||
|
|
||||||
def _resolve_callable(self, module_path: str):
|
def _resolve_callable(self, module_path: str):
|
||||||
@@ -84,8 +87,12 @@ class TaskScheduler:
|
|||||||
# 如果所有尝试均失败，则抛出最后的错误
|
# 如果所有尝试均失败，则抛出最后的错误
|
||||||
raise ImportError(f"模块 {module_path} 导入/解析失败: {str(last_import_error)}")
|
raise ImportError(f"模块 {module_path} 导入/解析失败: {str(last_import_error)}")
|
||||||
|
|
||||||
def check_and_run_tasks(self) -> Dict[str, int]:
|
def check_and_run_tasks(self, print_empty_status: bool = False) -> Dict[str, int]:
|
||||||
"""检查并执行所有到期的任务，优化空任务处理和异常容错"""
|
"""检查并执行所有到期的任务，优化空任务处理和异常容错
|
||||||
|
|
||||||
|
Args:
|
||||||
|
print_empty_status: 是否打印空任务状态（默认False，避免频繁输出）
|
||||||
|
"""
|
||||||
result = {'总任务数': 0, '成功': 0, '失败': 0}
|
result = {'总任务数': 0, '成功': 0, '失败': 0}
|
||||||
|
|
||||||
try:
|
try:
|
||||||
@@ -106,8 +113,9 @@ class TaskScheduler:
|
|||||||
|
|
||||||
result['总任务数'] = len(tasks_df)
|
result['总任务数'] = len(tasks_df)
|
||||||
if tasks_df.empty:
|
if tasks_df.empty:
|
||||||
# 空任务时输出INFO级日志，明确提示状态
|
# 空任务时根据参数决定是否输出
|
||||||
print(f"当前没有到期的任务，等待新任务加入...{now.strftime('%Y-%m-%d %H:%M:%S')}")
|
if print_empty_status:
|
||||||
|
print(f"当前没有到期的任务，等待新任务加入...{now.strftime('%Y-%m-%d %H:%M:%S')}")
|
||||||
return result
|
return result
|
||||||
|
|
||||||
# 并发执行任务
|
# 并发执行任务
|
||||||
@@ -128,6 +136,12 @@ class TaskScheduler:
|
|||||||
log.error(f"任务线程执行失败: {str(e)}", exc_info=True)
|
log.error(f"任务线程执行失败: {str(e)}", exc_info=True)
|
||||||
result['失败'] += 1
|
result['失败'] += 1
|
||||||
|
|
||||||
|
# 更新小时统计
|
||||||
|
with self.hourly_stats_lock:
|
||||||
|
self.hourly_stats['成功'] += result['成功']
|
||||||
|
self.hourly_stats['失败'] += result['失败']
|
||||||
|
self.hourly_stats['总数'] += result['总任务数']
|
||||||
|
|
||||||
log.info(
|
log.info(
|
||||||
"任务调度周期完成",
|
"任务调度周期完成",
|
||||||
总任务数=result['总任务数'],
|
总任务数=result['总任务数'],
|
||||||
@@ -419,4 +433,12 @@ class TaskScheduler:
|
|||||||
|
|
||||||
except Exception as e:
|
except Exception as e:
|
||||||
log.error(f"查询待执行任务失败，将重试: {str(e)}", exc_info=True)
|
log.error(f"查询待执行任务失败，将重试: {str(e)}", exc_info=True)
|
||||||
return []
|
return []
|
||||||
|
|
||||||
|
def get_and_reset_hourly_stats(self) -> Dict[str, int]:
|
||||||
|
"""获取并重置小时统计数据（用于每小时统计）"""
|
||||||
|
with self.hourly_stats_lock:
|
||||||
|
stats = self.hourly_stats.copy()
|
||||||
|
# 重置统计
|
||||||
|
self.hourly_stats = {'成功': 0, '失败': 0, '总数': 0}
|
||||||
|
return stats
|
||||||
+472
-289
@@ -10,14 +10,25 @@
|
|||||||
},
|
},
|
||||||
{
|
{
|
||||||
"cell_type": "code",
|
"cell_type": "code",
|
||||||
|
"execution_count": 1,
|
||||||
"id": "initial_id",
|
"id": "initial_id",
|
||||||
"metadata": {
|
"metadata": {
|
||||||
"collapsed": true,
|
|
||||||
"ExecuteTime": {
|
"ExecuteTime": {
|
||||||
"end_time": "2025-10-17T05:43:18.381936Z",
|
"end_time": "2025-10-17T05:43:18.381936Z",
|
||||||
"start_time": "2025-10-17T05:43:15.265036Z"
|
"start_time": "2025-10-17T05:43:15.265036Z"
|
||||||
}
|
},
|
||||||
|
"collapsed": true
|
||||||
},
|
},
|
||||||
|
"outputs": [
|
||||||
|
{
|
||||||
|
"name": "stdout",
|
||||||
|
"output_type": "stream",
|
||||||
|
"text": [
|
||||||
|
"PROJECT_ROOT = d:\\Idea Project\\intelligence_system\n",
|
||||||
|
"\u001b[32m2025-10-23 16:56:55\u001b[0m | \u001b[1mINFO \u001b[0m | \u001b[36mtask_scheduler\u001b[0m - \u001b[1m任务调度器已初始化，最大工作线程数: 5\u001b[0m\n"
|
||||||
|
]
|
||||||
|
}
|
||||||
|
],
|
||||||
"source": [
|
"source": [
|
||||||
"# 使 Notebook 可从项目根导入\n",
|
"# 使 Notebook 可从项目根导入\n",
|
||||||
"import sys\n",
|
"import sys\n",
|
||||||
@@ -116,6 +127,78 @@
|
|||||||
" log.exception(\"手动执行任务失败\")\n",
|
" log.exception(\"手动执行任务失败\")\n",
|
||||||
" return False\n",
|
" return False\n",
|
||||||
"\n",
|
"\n",
|
||||||
|
" def run_task_synchronously(self, task_id: int) -> dict:\n",
|
||||||
|
" \"\"\"同步执行任务并返回详细结果（用于Notebook中查看执行过程）\"\"\"\n",
|
||||||
|
" import time\n",
|
||||||
|
" import sys\n",
|
||||||
|
" from io import StringIO\n",
|
||||||
|
" \n",
|
||||||
|
" task = self.get_task_by_id(task_id)\n",
|
||||||
|
" if not task:\n",
|
||||||
|
" return {\n",
|
||||||
|
" 'success': False,\n",
|
||||||
|
" 'error': f'未找到任务ID: {task_id}',\n",
|
||||||
|
" 'output': ''\n",
|
||||||
|
" }\n",
|
||||||
|
" \n",
|
||||||
|
" # 捕获标准输出\n",
|
||||||
|
" old_stdout = sys.stdout\n",
|
||||||
|
" sys.stdout = output_buffer = StringIO()\n",
|
||||||
|
" \n",
|
||||||
|
" start_time = time.time()\n",
|
||||||
|
" success = False\n",
|
||||||
|
" error_msg = None\n",
|
||||||
|
" \n",
|
||||||
|
" try:\n",
|
||||||
|
" # 直接同步执行任务逻辑\n",
|
||||||
|
" self.scheduler._execute_task_logic(task)\n",
|
||||||
|
" success = True\n",
|
||||||
|
" \n",
|
||||||
|
" # 更新任务状态\n",
|
||||||
|
" next_run_time = self.scheduler._calculate_next_run_time(\n",
|
||||||
|
" cron_expr=task['cron_expression'],\n",
|
||||||
|
" time_zone=task.get('time_zone', 'Asia/Shanghai')\n",
|
||||||
|
" )\n",
|
||||||
|
" \n",
|
||||||
|
" self.scheduler._update_task_status(task['task_id'], {\n",
|
||||||
|
" 'last_run_status': 'success',\n",
|
||||||
|
" 'is_running': 0,\n",
|
||||||
|
" 'run_count': task['run_count'] + 1,\n",
|
||||||
|
" 'next_run_time': next_run_time\n",
|
||||||
|
" })\n",
|
||||||
|
" \n",
|
||||||
|
" except Exception as e:\n",
|
||||||
|
" success = False\n",
|
||||||
|
" error_msg = str(e)\n",
|
||||||
|
" log.exception(f\"任务执行失败: {task['task_name']}\")\n",
|
||||||
|
" \n",
|
||||||
|
" # 更新失败状态\n",
|
||||||
|
" try:\n",
|
||||||
|
" next_retry_time = datetime.now() + pd.Timedelta(minutes=15)\n",
|
||||||
|
" self.scheduler._update_task_status(task['task_id'], {\n",
|
||||||
|
" 'last_run_status': 'failed',\n",
|
||||||
|
" 'is_running': 0,\n",
|
||||||
|
" 'next_run_time': next_retry_time\n",
|
||||||
|
" })\n",
|
||||||
|
" except Exception:\n",
|
||||||
|
" pass\n",
|
||||||
|
" \n",
|
||||||
|
" finally:\n",
|
||||||
|
" # 恢复标准输出\n",
|
||||||
|
" sys.stdout = old_stdout\n",
|
||||||
|
" output_text = output_buffer.getvalue()\n",
|
||||||
|
" \n",
|
||||||
|
" execution_time = time.time() - start_time\n",
|
||||||
|
" \n",
|
||||||
|
" return {\n",
|
||||||
|
" 'success': success,\n",
|
||||||
|
" 'task_name': task['task_name'],\n",
|
||||||
|
" 'task_id': task['task_id'],\n",
|
||||||
|
" 'execution_time': execution_time,\n",
|
||||||
|
" 'output': output_text,\n",
|
||||||
|
" 'error': error_msg\n",
|
||||||
|
" }\n",
|
||||||
|
"\n",
|
||||||
"# 在这里创建 manager（供后续单元使用）\n",
|
"# 在这里创建 manager（供后续单元使用）\n",
|
||||||
"manager = TaskManager(scheduler)\n",
|
"manager = TaskManager(scheduler)\n",
|
||||||
"\n",
|
"\n",
|
||||||
@@ -134,18 +217,7 @@
|
|||||||
" except Exception:\n",
|
" except Exception:\n",
|
||||||
" pass\n",
|
" pass\n",
|
||||||
" return str(dt)"
|
" return str(dt)"
|
||||||
],
|
]
|
||||||
"outputs": [
|
|
||||||
{
|
|
||||||
"name": "stdout",
|
|
||||||
"output_type": "stream",
|
|
||||||
"text": [
|
|
||||||
"PROJECT_ROOT = D:\\Idea Project\\intelligence_system\n",
|
|
||||||
"\u001B[32m2025-10-17 13:43:18\u001B[0m | \u001B[1mINFO \u001B[0m | \u001B[36mtask_scheduler\u001B[0m - \u001B[1m任务调度器已初始化，最大工作线程数: 5\u001B[0m\n"
|
|
||||||
]
|
|
||||||
}
|
|
||||||
],
|
|
||||||
"execution_count": 1
|
|
||||||
},
|
},
|
||||||
{
|
{
|
||||||
"cell_type": "markdown",
|
"cell_type": "markdown",
|
||||||
@@ -157,6 +229,7 @@
|
|||||||
},
|
},
|
||||||
{
|
{
|
||||||
"cell_type": "code",
|
"cell_type": "code",
|
||||||
|
"execution_count": 2,
|
||||||
"id": "7b020af55972643",
|
"id": "7b020af55972643",
|
||||||
"metadata": {
|
"metadata": {
|
||||||
"ExecuteTime": {
|
"ExecuteTime": {
|
||||||
@@ -164,73 +237,28 @@
|
|||||||
"start_time": "2025-10-17T05:43:18.394863Z"
|
"start_time": "2025-10-17T05:43:18.394863Z"
|
||||||
}
|
}
|
||||||
},
|
},
|
||||||
"source": [
|
|
||||||
"# 列出所有任务（包括已禁用的）\n",
|
|
||||||
"def list_tasks(active_only=True):\n",
|
|
||||||
" tasks = manager.get_all_tasks(active_only)\n",
|
|
||||||
" if not tasks:\n",
|
|
||||||
" display(Markdown(\"### 没有找到任务\"))\n",
|
|
||||||
" return None\n",
|
|
||||||
"\n",
|
|
||||||
" df = pd.DataFrame(tasks)\n",
|
|
||||||
"\n",
|
|
||||||
" # 格式化日期列\n",
|
|
||||||
" if 'last_run_time' in df.columns:\n",
|
|
||||||
" df['last_run_time'] = df['last_run_time'].apply(format_datetime)\n",
|
|
||||||
" if 'next_run_time' in df.columns:\n",
|
|
||||||
" df['next_run_time'] = df['next_run_time'].apply(format_datetime)\n",
|
|
||||||
"\n",
|
|
||||||
" # 重命名列名\n",
|
|
||||||
" df = df.rename(columns={\n",
|
|
||||||
" 'task_id': '任务ID',\n",
|
|
||||||
" 'task_name': '任务名称',\n",
|
|
||||||
" 'task_type': '任务类型',\n",
|
|
||||||
" 'module_path': '模块路径',\n",
|
|
||||||
" 'cron_expression': 'Cron表达式',\n",
|
|
||||||
" 'time_zone': '时区',\n",
|
|
||||||
" 'last_run_time': '最后运行时间',\n",
|
|
||||||
" 'next_run_time': '下次运行时间',\n",
|
|
||||||
" 'last_run_status': '运行状态',\n",
|
|
||||||
" 'is_active': '是否活跃',\n",
|
|
||||||
" 'run_count': '运行次数'\n",
|
|
||||||
" })\n",
|
|
||||||
"\n",
|
|
||||||
" display(Markdown(\"### 任务列表\"))\n",
|
|
||||||
" display(HTML(df.to_html(index=False)))\n",
|
|
||||||
" return df\n",
|
|
||||||
"\n",
|
|
||||||
"# 执行：列出所有任务（包括已禁用）\n",
|
|
||||||
"list_tasks(active_only=False)\n",
|
|
||||||
"\n",
|
|
||||||
"# 或者：只列出活跃任务\n",
|
|
||||||
"# list_tasks(active_only=True)"
|
|
||||||
],
|
|
||||||
"outputs": [
|
"outputs": [
|
||||||
{
|
{
|
||||||
"name": "stdout",
|
"name": "stdout",
|
||||||
"output_type": "stream",
|
"output_type": "stream",
|
||||||
"text": [
|
"text": [
|
||||||
"\u001B[32m2025-10-17 13:43:18\u001B[0m | \u001B[1mINFO \u001B[0m | \u001B[36mmysql_agent\u001B[0m - \u001B[1m查询执行成功\u001B[0m\n"
|
"\u001b[32m2025-10-17 13:43:18\u001b[0m | \u001b[1mINFO \u001b[0m | \u001b[36mmysql_agent\u001b[0m - \u001b[1m查询执行成功\u001b[0m\n"
|
||||||
]
|
]
|
||||||
},
|
},
|
||||||
{
|
{
|
||||||
"data": {
|
"data": {
|
||||||
|
"text/markdown": [
|
||||||
|
"### 任务列表"
|
||||||
|
],
|
||||||
"text/plain": [
|
"text/plain": [
|
||||||
"<IPython.core.display.Markdown object>"
|
"<IPython.core.display.Markdown object>"
|
||||||
],
|
]
|
||||||
"text/markdown": "### 任务列表"
|
|
||||||
},
|
},
|
||||||
"metadata": {},
|
"metadata": {},
|
||||||
"output_type": "display_data",
|
"output_type": "display_data"
|
||||||
"jetTransient": {
|
|
||||||
"display_id": null
|
|
||||||
}
|
|
||||||
},
|
},
|
||||||
{
|
{
|
||||||
"data": {
|
"data": {
|
||||||
"text/plain": [
|
|
||||||
"<IPython.core.display.HTML object>"
|
|
||||||
],
|
|
||||||
"text/html": [
|
"text/html": [
|
||||||
"<table border=\"1\" class=\"dataframe\">\n",
|
"<table border=\"1\" class=\"dataframe\">\n",
|
||||||
" <thead>\n",
|
" <thead>\n",
|
||||||
@@ -270,26 +298,16 @@
|
|||||||
" </tr>\n",
|
" </tr>\n",
|
||||||
" </tbody>\n",
|
" </tbody>\n",
|
||||||
"</table>"
|
"</table>"
|
||||||
|
],
|
||||||
|
"text/plain": [
|
||||||
|
"<IPython.core.display.HTML object>"
|
||||||
]
|
]
|
||||||
},
|
},
|
||||||
"metadata": {},
|
"metadata": {},
|
||||||
"output_type": "display_data",
|
"output_type": "display_data"
|
||||||
"jetTransient": {
|
|
||||||
"display_id": null
|
|
||||||
}
|
|
||||||
},
|
},
|
||||||
{
|
{
|
||||||
"data": {
|
"data": {
|
||||||
"text/plain": [
|
|
||||||
" 任务ID 任务名称 任务类型 模块路径 \\\n",
|
|
||||||
"0 1 RSS新闻订阅 collector collectors.rss_subscriptions.NewsAPIClient \n",
|
|
||||||
"\n",
|
|
||||||
" Cron表达式 时区 下次运行时间 最后运行时间 \\\n",
|
|
||||||
"0 5 0 * * * Asia/Shanghai 2025-10-18 00:05:00 2025-10-17 00:05:07 \n",
|
|
||||||
"\n",
|
|
||||||
" 运行状态 运行次数 是否活跃 is_running created_at updated_at \n",
|
|
||||||
"0 success 4 1 0 2025-10-16 15:47:34 2025-10-17 00:05:08 "
|
|
||||||
],
|
|
||||||
"text/html": [
|
"text/html": [
|
||||||
"<div>\n",
|
"<div>\n",
|
||||||
"<style scoped>\n",
|
"<style scoped>\n",
|
||||||
@@ -346,6 +364,16 @@
|
|||||||
" </tbody>\n",
|
" </tbody>\n",
|
||||||
"</table>\n",
|
"</table>\n",
|
||||||
"</div>"
|
"</div>"
|
||||||
|
],
|
||||||
|
"text/plain": [
|
||||||
|
" 任务ID 任务名称 任务类型 模块路径 \\\n",
|
||||||
|
"0 1 RSS新闻订阅 collector collectors.rss_subscriptions.NewsAPIClient \n",
|
||||||
|
"\n",
|
||||||
|
" Cron表达式 时区 下次运行时间 最后运行时间 \\\n",
|
||||||
|
"0 5 0 * * * Asia/Shanghai 2025-10-18 00:05:00 2025-10-17 00:05:07 \n",
|
||||||
|
"\n",
|
||||||
|
" 运行状态 运行次数 是否活跃 is_running created_at updated_at \n",
|
||||||
|
"0 success 4 1 0 2025-10-16 15:47:34 2025-10-17 00:05:08 "
|
||||||
]
|
]
|
||||||
},
|
},
|
||||||
"execution_count": 2,
|
"execution_count": 2,
|
||||||
@@ -353,7 +381,47 @@
|
|||||||
"output_type": "execute_result"
|
"output_type": "execute_result"
|
||||||
}
|
}
|
||||||
],
|
],
|
||||||
"execution_count": 2
|
"source": [
|
||||||
|
"# 列出所有任务（包括已禁用的）\n",
|
||||||
|
"def list_tasks(active_only=True):\n",
|
||||||
|
" tasks = manager.get_all_tasks(active_only)\n",
|
||||||
|
" if not tasks:\n",
|
||||||
|
" display(Markdown(\"### 没有找到任务\"))\n",
|
||||||
|
" return None\n",
|
||||||
|
"\n",
|
||||||
|
" df = pd.DataFrame(tasks)\n",
|
||||||
|
"\n",
|
||||||
|
" # 格式化日期列\n",
|
||||||
|
" if 'last_run_time' in df.columns:\n",
|
||||||
|
" df['last_run_time'] = df['last_run_time'].apply(format_datetime)\n",
|
||||||
|
" if 'next_run_time' in df.columns:\n",
|
||||||
|
" df['next_run_time'] = df['next_run_time'].apply(format_datetime)\n",
|
||||||
|
"\n",
|
||||||
|
" # 重命名列名\n",
|
||||||
|
" df = df.rename(columns={\n",
|
||||||
|
" 'task_id': '任务ID',\n",
|
||||||
|
" 'task_name': '任务名称',\n",
|
||||||
|
" 'task_type': '任务类型',\n",
|
||||||
|
" 'module_path': '模块路径',\n",
|
||||||
|
" 'cron_expression': 'Cron表达式',\n",
|
||||||
|
" 'time_zone': '时区',\n",
|
||||||
|
" 'last_run_time': '最后运行时间',\n",
|
||||||
|
" 'next_run_time': '下次运行时间',\n",
|
||||||
|
" 'last_run_status': '运行状态',\n",
|
||||||
|
" 'is_active': '是否活跃',\n",
|
||||||
|
" 'run_count': '运行次数'\n",
|
||||||
|
" })\n",
|
||||||
|
"\n",
|
||||||
|
" display(Markdown(\"### 任务列表\"))\n",
|
||||||
|
" display(HTML(df.to_html(index=False)))\n",
|
||||||
|
" return df\n",
|
||||||
|
"\n",
|
||||||
|
"# 执行：列出所有任务（包括已禁用）\n",
|
||||||
|
"list_tasks(active_only=False)\n",
|
||||||
|
"\n",
|
||||||
|
"# 或者：只列出活跃任务\n",
|
||||||
|
"# list_tasks(active_only=True)"
|
||||||
|
]
|
||||||
},
|
},
|
||||||
{
|
{
|
||||||
"cell_type": "markdown",
|
"cell_type": "markdown",
|
||||||
@@ -365,6 +433,7 @@
|
|||||||
},
|
},
|
||||||
{
|
{
|
||||||
"cell_type": "code",
|
"cell_type": "code",
|
||||||
|
"execution_count": 3,
|
||||||
"id": "eab90de72c35429e",
|
"id": "eab90de72c35429e",
|
||||||
"metadata": {
|
"metadata": {
|
||||||
"ExecuteTime": {
|
"ExecuteTime": {
|
||||||
@@ -372,6 +441,62 @@
|
|||||||
"start_time": "2025-10-17T05:43:26.071398Z"
|
"start_time": "2025-10-17T05:43:26.071398Z"
|
||||||
}
|
}
|
||||||
},
|
},
|
||||||
|
"outputs": [
|
||||||
|
{
|
||||||
|
"name": "stdout",
|
||||||
|
"output_type": "stream",
|
||||||
|
"text": [
|
||||||
|
"\u001b[32m2025-10-17 13:43:26\u001b[0m | \u001b[1mINFO \u001b[0m | \u001b[36mmysql_agent\u001b[0m - \u001b[1m查询执行成功\u001b[0m\n"
|
||||||
|
]
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"data": {
|
||||||
|
"text/markdown": [
|
||||||
|
"### 任务详情\n",
|
||||||
|
"**任务ID**: 1\n",
|
||||||
|
"**任务名称**: RSS新闻订阅\n",
|
||||||
|
"**任务类型**: collector\n",
|
||||||
|
"**模块路径**: collectors.rss_subscriptions.NewsAPIClient\n",
|
||||||
|
"**Cron表达式**: 5 0 * * *\n",
|
||||||
|
"**时区**: Asia/Shanghai\n",
|
||||||
|
"**最后运行时间**: 2025-10-17 00:05:07\n",
|
||||||
|
"**下次运行时间**: 2025-10-18 00:05:00\n",
|
||||||
|
"**运行状态**: success\n",
|
||||||
|
"**是否活跃**: 是\n",
|
||||||
|
"**运行次数**: 4\n",
|
||||||
|
"**创建时间**: 2025-10-16 15:47:34"
|
||||||
|
],
|
||||||
|
"text/plain": [
|
||||||
|
"<IPython.core.display.Markdown object>"
|
||||||
|
]
|
||||||
|
},
|
||||||
|
"metadata": {},
|
||||||
|
"output_type": "display_data"
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"data": {
|
||||||
|
"text/plain": [
|
||||||
|
"{'task_id': 1,\n",
|
||||||
|
" 'task_name': 'RSS新闻订阅',\n",
|
||||||
|
" 'task_type': 'collector',\n",
|
||||||
|
" 'module_path': 'collectors.rss_subscriptions.NewsAPIClient',\n",
|
||||||
|
" 'cron_expression': '5 0 * * *',\n",
|
||||||
|
" 'time_zone': 'Asia/Shanghai',\n",
|
||||||
|
" 'next_run_time': Timestamp('2025-10-18 00:05:00'),\n",
|
||||||
|
" 'last_run_time': Timestamp('2025-10-17 00:05:07'),\n",
|
||||||
|
" 'last_run_status': 'success',\n",
|
||||||
|
" 'run_count': 4,\n",
|
||||||
|
" 'is_active': 1,\n",
|
||||||
|
" 'is_running': 0,\n",
|
||||||
|
" 'created_at': Timestamp('2025-10-16 15:47:34'),\n",
|
||||||
|
" 'updated_at': Timestamp('2025-10-17 00:05:08')}"
|
||||||
|
]
|
||||||
|
},
|
||||||
|
"execution_count": 3,
|
||||||
|
"metadata": {},
|
||||||
|
"output_type": "execute_result"
|
||||||
|
}
|
||||||
|
],
|
||||||
"source": [
|
"source": [
|
||||||
"# 查看指定任务的详情\n",
|
"# 查看指定任务的详情\n",
|
||||||
"def show_task_details(task_id):\n",
|
"def show_task_details(task_id):\n",
|
||||||
@@ -399,53 +524,7 @@
|
|||||||
"\n",
|
"\n",
|
||||||
"# 执行：查看任务ID为1的详情（替换为实际ID）\n",
|
"# 执行：查看任务ID为1的详情（替换为实际ID）\n",
|
||||||
"show_task_details(1)"
|
"show_task_details(1)"
|
||||||
],
|
]
|
||||||
"outputs": [
|
|
||||||
{
|
|
||||||
"name": "stdout",
|
|
||||||
"output_type": "stream",
|
|
||||||
"text": [
|
|
||||||
"\u001B[32m2025-10-17 13:43:26\u001B[0m | \u001B[1mINFO \u001B[0m | \u001B[36mmysql_agent\u001B[0m - \u001B[1m查询执行成功\u001B[0m\n"
|
|
||||||
]
|
|
||||||
},
|
|
||||||
{
|
|
||||||
"data": {
|
|
||||||
"text/plain": [
|
|
||||||
"<IPython.core.display.Markdown object>"
|
|
||||||
],
|
|
||||||
"text/markdown": "### 任务详情\n**任务ID**: 1\n**任务名称**: RSS新闻订阅\n**任务类型**: collector\n**模块路径**: collectors.rss_subscriptions.NewsAPIClient\n**Cron表达式**: 5 0 * * *\n**时区**: Asia/Shanghai\n**最后运行时间**: 2025-10-17 00:05:07\n**下次运行时间**: 2025-10-18 00:05:00\n**运行状态**: success\n**是否活跃**: 是\n**运行次数**: 4\n**创建时间**: 2025-10-16 15:47:34"
|
|
||||||
},
|
|
||||||
"metadata": {},
|
|
||||||
"output_type": "display_data",
|
|
||||||
"jetTransient": {
|
|
||||||
"display_id": null
|
|
||||||
}
|
|
||||||
},
|
|
||||||
{
|
|
||||||
"data": {
|
|
||||||
"text/plain": [
|
|
||||||
"{'task_id': 1,\n",
|
|
||||||
" 'task_name': 'RSS新闻订阅',\n",
|
|
||||||
" 'task_type': 'collector',\n",
|
|
||||||
" 'module_path': 'collectors.rss_subscriptions.NewsAPIClient',\n",
|
|
||||||
" 'cron_expression': '5 0 * * *',\n",
|
|
||||||
" 'time_zone': 'Asia/Shanghai',\n",
|
|
||||||
" 'next_run_time': Timestamp('2025-10-18 00:05:00'),\n",
|
|
||||||
" 'last_run_time': Timestamp('2025-10-17 00:05:07'),\n",
|
|
||||||
" 'last_run_status': 'success',\n",
|
|
||||||
" 'run_count': 4,\n",
|
|
||||||
" 'is_active': 1,\n",
|
|
||||||
" 'is_running': 0,\n",
|
|
||||||
" 'created_at': Timestamp('2025-10-16 15:47:34'),\n",
|
|
||||||
" 'updated_at': Timestamp('2025-10-17 00:05:08')}"
|
|
||||||
]
|
|
||||||
},
|
|
||||||
"execution_count": 3,
|
|
||||||
"metadata": {},
|
|
||||||
"output_type": "execute_result"
|
|
||||||
}
|
|
||||||
],
|
|
||||||
"execution_count": 3
|
|
||||||
},
|
},
|
||||||
{
|
{
|
||||||
"cell_type": "markdown",
|
"cell_type": "markdown",
|
||||||
@@ -473,8 +552,8 @@
|
|||||||
"name": "stdout",
|
"name": "stdout",
|
||||||
"output_type": "stream",
|
"output_type": "stream",
|
||||||
"text": [
|
"text": [
|
||||||
"\u001B[32m2025-10-16 15:47:34\u001B[0m | \u001B[1mINFO \u001B[0m | \u001B[36mmysql_agent\u001B[0m - \u001B[1m查询执行成功\u001B[0m\n",
|
"\u001b[32m2025-10-16 15:47:34\u001b[0m | \u001b[1mINFO \u001b[0m | \u001b[36mmysql_agent\u001b[0m - \u001b[1m查询执行成功\u001b[0m\n",
|
||||||
"\u001B[32m2025-10-16 15:47:34\u001B[0m | \u001B[1mINFO \u001B[0m | \u001B[36mtask_scheduler\u001B[0m - \u001B[1m新任务添加成功\u001B[0m\n"
|
"\u001b[32m2025-10-16 15:47:34\u001b[0m | \u001b[1mINFO \u001b[0m | \u001b[36mtask_scheduler\u001b[0m - \u001b[1m新任务添加成功\u001b[0m\n"
|
||||||
]
|
]
|
||||||
},
|
},
|
||||||
{
|
{
|
||||||
@@ -550,6 +629,7 @@
|
|||||||
},
|
},
|
||||||
{
|
{
|
||||||
"cell_type": "code",
|
"cell_type": "code",
|
||||||
|
"execution_count": 4,
|
||||||
"id": "c892fd8ad2f0dd9d",
|
"id": "c892fd8ad2f0dd9d",
|
||||||
"metadata": {
|
"metadata": {
|
||||||
"ExecuteTime": {
|
"ExecuteTime": {
|
||||||
@@ -557,6 +637,61 @@
|
|||||||
"start_time": "2025-10-17T05:44:18.980345Z"
|
"start_time": "2025-10-17T05:44:18.980345Z"
|
||||||
}
|
}
|
||||||
},
|
},
|
||||||
|
"outputs": [
|
||||||
|
{
|
||||||
|
"data": {
|
||||||
|
"text/markdown": [
|
||||||
|
"### 任务ID 1 更新成功"
|
||||||
|
],
|
||||||
|
"text/plain": [
|
||||||
|
"<IPython.core.display.Markdown object>"
|
||||||
|
]
|
||||||
|
},
|
||||||
|
"metadata": {},
|
||||||
|
"output_type": "display_data"
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"name": "stdout",
|
||||||
|
"output_type": "stream",
|
||||||
|
"text": [
|
||||||
|
"\u001b[32m2025-10-17 13:44:19\u001b[0m | \u001b[1mINFO \u001b[0m | \u001b[36mmysql_agent\u001b[0m - \u001b[1m查询执行成功\u001b[0m\n"
|
||||||
|
]
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"data": {
|
||||||
|
"text/markdown": [
|
||||||
|
"### 任务详情\n",
|
||||||
|
"**任务ID**: 1\n",
|
||||||
|
"**任务名称**: RSS新闻订阅\n",
|
||||||
|
"**任务类型**: collector\n",
|
||||||
|
"**模块路径**: collectors.rss_subscriptions.NewsAPIClient\n",
|
||||||
|
"**Cron表达式**: 5 * * * *\n",
|
||||||
|
"**时区**: Asia/Shanghai\n",
|
||||||
|
"**最后运行时间**: 2025-10-17 00:05:07\n",
|
||||||
|
"**下次运行时间**: 2025-10-18 00:05:00\n",
|
||||||
|
"**运行状态**: success\n",
|
||||||
|
"**是否活跃**: 是\n",
|
||||||
|
"**运行次数**: 4\n",
|
||||||
|
"**创建时间**: 2025-10-16 15:47:34"
|
||||||
|
],
|
||||||
|
"text/plain": [
|
||||||
|
"<IPython.core.display.Markdown object>"
|
||||||
|
]
|
||||||
|
},
|
||||||
|
"metadata": {},
|
||||||
|
"output_type": "display_data"
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"data": {
|
||||||
|
"text/plain": [
|
||||||
|
"True"
|
||||||
|
]
|
||||||
|
},
|
||||||
|
"execution_count": 4,
|
||||||
|
"metadata": {},
|
||||||
|
"output_type": "execute_result"
|
||||||
|
}
|
||||||
|
],
|
||||||
"source": [
|
"source": [
|
||||||
"# 更新任务属性\n",
|
"# 更新任务属性\n",
|
||||||
"def update_task(task_id, **kwargs):\n",
|
"def update_task(task_id, **kwargs):\n",
|
||||||
@@ -589,53 +724,7 @@
|
|||||||
"\n",
|
"\n",
|
||||||
"# 执行：同时更新多个属性（名称和Cron表达式）\n",
|
"# 执行：同时更新多个属性（名称和Cron表达式）\n",
|
||||||
"# update_task(1, name=\"每日早间新闻采集\", cron=\"0 8 * * *\")"
|
"# update_task(1, name=\"每日早间新闻采集\", cron=\"0 8 * * *\")"
|
||||||
],
|
]
|
||||||
"outputs": [
|
|
||||||
{
|
|
||||||
"data": {
|
|
||||||
"text/plain": [
|
|
||||||
"<IPython.core.display.Markdown object>"
|
|
||||||
],
|
|
||||||
"text/markdown": "### 任务ID 1 更新成功"
|
|
||||||
},
|
|
||||||
"metadata": {},
|
|
||||||
"output_type": "display_data",
|
|
||||||
"jetTransient": {
|
|
||||||
"display_id": null
|
|
||||||
}
|
|
||||||
},
|
|
||||||
{
|
|
||||||
"name": "stdout",
|
|
||||||
"output_type": "stream",
|
|
||||||
"text": [
|
|
||||||
"\u001B[32m2025-10-17 13:44:19\u001B[0m | \u001B[1mINFO \u001B[0m | \u001B[36mmysql_agent\u001B[0m - \u001B[1m查询执行成功\u001B[0m\n"
|
|
||||||
]
|
|
||||||
},
|
|
||||||
{
|
|
||||||
"data": {
|
|
||||||
"text/plain": [
|
|
||||||
"<IPython.core.display.Markdown object>"
|
|
||||||
],
|
|
||||||
"text/markdown": "### 任务详情\n**任务ID**: 1\n**任务名称**: RSS新闻订阅\n**任务类型**: collector\n**模块路径**: collectors.rss_subscriptions.NewsAPIClient\n**Cron表达式**: 5 * * * *\n**时区**: Asia/Shanghai\n**最后运行时间**: 2025-10-17 00:05:07\n**下次运行时间**: 2025-10-18 00:05:00\n**运行状态**: success\n**是否活跃**: 是\n**运行次数**: 4\n**创建时间**: 2025-10-16 15:47:34"
|
|
||||||
},
|
|
||||||
"metadata": {},
|
|
||||||
"output_type": "display_data",
|
|
||||||
"jetTransient": {
|
|
||||||
"display_id": null
|
|
||||||
}
|
|
||||||
},
|
|
||||||
{
|
|
||||||
"data": {
|
|
||||||
"text/plain": [
|
|
||||||
"True"
|
|
||||||
]
|
|
||||||
},
|
|
||||||
"execution_count": 4,
|
|
||||||
"metadata": {},
|
|
||||||
"output_type": "execute_result"
|
|
||||||
}
|
|
||||||
],
|
|
||||||
"execution_count": 4
|
|
||||||
},
|
},
|
||||||
{
|
{
|
||||||
"cell_type": "markdown",
|
"cell_type": "markdown",
|
||||||
@@ -702,6 +791,7 @@
|
|||||||
},
|
},
|
||||||
{
|
{
|
||||||
"cell_type": "code",
|
"cell_type": "code",
|
||||||
|
"execution_count": 2,
|
||||||
"id": "94892f4134316f8e",
|
"id": "94892f4134316f8e",
|
||||||
"metadata": {
|
"metadata": {
|
||||||
"ExecuteTime": {
|
"ExecuteTime": {
|
||||||
@@ -709,8 +799,177 @@
|
|||||||
"start_time": "2025-10-17T05:44:35.084369Z"
|
"start_time": "2025-10-17T05:44:35.084369Z"
|
||||||
}
|
}
|
||||||
},
|
},
|
||||||
|
"outputs": [
|
||||||
|
{
|
||||||
|
"data": {
|
||||||
|
"text/markdown": [
|
||||||
|
"### 开始执行任务ID 2"
|
||||||
|
],
|
||||||
|
"text/plain": [
|
||||||
|
"<IPython.core.display.Markdown object>"
|
||||||
|
]
|
||||||
|
},
|
||||||
|
"metadata": {},
|
||||||
|
"output_type": "display_data"
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"data": {
|
||||||
|
"text/markdown": [
|
||||||
|
"---"
|
||||||
|
],
|
||||||
|
"text/plain": [
|
||||||
|
"<IPython.core.display.Markdown object>"
|
||||||
|
]
|
||||||
|
},
|
||||||
|
"metadata": {},
|
||||||
|
"output_type": "display_data"
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"name": "stdout",
|
||||||
|
"output_type": "stream",
|
||||||
|
"text": [
|
||||||
|
"\u001b[32m2025-10-23 16:57:20\u001b[0m | \u001b[1mINFO \u001b[0m | \u001b[36mmysql_agent\u001b[0m - \u001b[1m查询执行成功\u001b[0m\n",
|
||||||
|
"\u001b[32m2025-10-23 16:57:20\u001b[0m | \u001b[1mINFO \u001b[0m | \u001b[36mprocessor_rss_data\u001b[0m - \u001b[1mRSS数据处理器初始化完成\u001b[0m\n",
|
||||||
|
"\u001b[32m2025-10-23 16:57:20\u001b[0m | \u001b[1mINFO \u001b[0m | \u001b[36mprocessor_rss_data\u001b[0m - \u001b[1m开始处理RSS数据...\u001b[0m\n",
|
||||||
|
"\u001b[32m2025-10-23 16:57:21\u001b[0m | \u001b[1mINFO \u001b[0m | \u001b[36mprocessor_rss_data\u001b[0m - \u001b[1m成功加载 8 条未处理的RSS数据\u001b[0m\n",
|
||||||
|
"\u001b[32m2025-10-23 16:57:21\u001b[0m | \u001b[33m\u001b[1mWARNING \u001b[0m | \u001b[36mprocessor_rss_data\u001b[0m - \u001b[33m\u001b[1m停用词文件不存在: processors/stopwords.txt，使用默认停用词\u001b[0m\n",
|
||||||
|
"\u001b[32m2025-10-23 16:57:21\u001b[0m | \u001b[33m\u001b[1mWARNING \u001b[0m | \u001b[36mprocessor_rss_data\u001b[0m - \u001b[33m\u001b[1m关键词文件不存在: processors/keywords.txt\u001b[0m\n"
|
||||||
|
]
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"name": "stderr",
|
||||||
|
"output_type": "stream",
|
||||||
|
"text": [
|
||||||
|
"Building prefix dict from the default dictionary ...\n",
|
||||||
|
"Loading model from cache C:\\Users\\zy187\\AppData\\Local\\Temp\\jieba.cache\n",
|
||||||
|
"Loading model cost 0.609 seconds.\n",
|
||||||
|
"Prefix dict has been built successfully.\n"
|
||||||
|
]
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"name": "stdout",
|
||||||
|
"output_type": "stream",
|
||||||
|
"text": [
|
||||||
|
"\u001b[32m2025-10-23 16:57:21\u001b[0m | \u001b[1mINFO \u001b[0m | \u001b[36mprocessor_rss_data\u001b[0m - \u001b[1m数据处理完成，共处理 8 条记录\u001b[0m\n",
|
||||||
|
"\u001b[32m2025-10-23 16:57:21\u001b[0m | \u001b[1mINFO \u001b[0m | \u001b[36mprocessor_rss_data\u001b[0m - \u001b[1m过滤出 1 条汽车后市场相关新闻\u001b[0m\n",
|
||||||
|
"\u001b[32m2025-10-23 16:57:21\u001b[0m | \u001b[1mINFO \u001b[0m | \u001b[36mmysql_agent\u001b[0m - \u001b[1m表 processed_rss_data 插入结果汇总\u001b[0m\n",
|
||||||
|
"\u001b[32m2025-10-23 16:57:21\u001b[0m | \u001b[1mINFO \u001b[0m | \u001b[36mprocessor_rss_data\u001b[0m - \u001b[1m成功保存 1 条处理结果到数据库\u001b[0m\n",
|
||||||
|
"\u001b[32m2025-10-23 16:57:21\u001b[0m | \u001b[1mINFO \u001b[0m | \u001b[36mprocessor_rss_data\u001b[0m - \u001b[1m成功标记 8 条数据为已处理\u001b[0m\n",
|
||||||
|
"\u001b[32m2025-10-23 16:57:21\u001b[0m | \u001b[1mINFO \u001b[0m | \u001b[36mprocessor_rss_data\u001b[0m - \u001b[1mRSS数据处理完成\u001b[0m\n",
|
||||||
|
"\u001b[32m2025-10-23 16:57:21\u001b[0m | \u001b[1mINFO \u001b[0m | \u001b[36mtask_scheduler\u001b[0m - \u001b[1m任务执行完成，耗时: 1.19秒\u001b[0m\n"
|
||||||
|
]
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"data": {
|
||||||
|
"text/markdown": [
|
||||||
|
"**任务名称**: RSS基于规则数据处理"
|
||||||
|
],
|
||||||
|
"text/plain": [
|
||||||
|
"<IPython.core.display.Markdown object>"
|
||||||
|
]
|
||||||
|
},
|
||||||
|
"metadata": {},
|
||||||
|
"output_type": "display_data"
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"data": {
|
||||||
|
"text/markdown": [
|
||||||
|
"**任务ID**: 2"
|
||||||
|
],
|
||||||
|
"text/plain": [
|
||||||
|
"<IPython.core.display.Markdown object>"
|
||||||
|
]
|
||||||
|
},
|
||||||
|
"metadata": {},
|
||||||
|
"output_type": "display_data"
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"data": {
|
||||||
|
"text/markdown": [
|
||||||
|
"**执行时长**: 1.26 秒"
|
||||||
|
],
|
||||||
|
"text/plain": [
|
||||||
|
"<IPython.core.display.Markdown object>"
|
||||||
|
]
|
||||||
|
},
|
||||||
|
"metadata": {},
|
||||||
|
"output_type": "display_data"
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"data": {
|
||||||
|
"text/markdown": [
|
||||||
|
"---"
|
||||||
|
],
|
||||||
|
"text/plain": [
|
||||||
|
"<IPython.core.display.Markdown object>"
|
||||||
|
]
|
||||||
|
},
|
||||||
|
"metadata": {},
|
||||||
|
"output_type": "display_data"
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"data": {
|
||||||
|
"text/markdown": [
|
||||||
|
"### 📋 执行输出:"
|
||||||
|
],
|
||||||
|
"text/plain": [
|
||||||
|
"<IPython.core.display.Markdown object>"
|
||||||
|
]
|
||||||
|
},
|
||||||
|
"metadata": {},
|
||||||
|
"output_type": "display_data"
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"name": "stdout",
|
||||||
|
"output_type": "stream",
|
||||||
|
"text": [
|
||||||
|
"RSS数据处理完成！\n",
|
||||||
|
"处理统计: {'total_articles': 8, 'filtered_articles': 1, 'filter_rate': 0.125, 'processing_time': '2025-10-23 16:57:21', 'save_success': True, 'mark_success': True}\n",
|
||||||
|
"\n"
|
||||||
|
]
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"data": {
|
||||||
|
"text/markdown": [
|
||||||
|
"---"
|
||||||
|
],
|
||||||
|
"text/plain": [
|
||||||
|
"<IPython.core.display.Markdown object>"
|
||||||
|
]
|
||||||
|
},
|
||||||
|
"metadata": {},
|
||||||
|
"output_type": "display_data"
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"data": {
|
||||||
|
"text/markdown": [
|
||||||
|
"### ✅ 任务执行成功"
|
||||||
|
],
|
||||||
|
"text/plain": [
|
||||||
|
"<IPython.core.display.Markdown object>"
|
||||||
|
]
|
||||||
|
},
|
||||||
|
"metadata": {},
|
||||||
|
"output_type": "display_data"
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"data": {
|
||||||
|
"text/plain": [
|
||||||
|
"{'success': True,\n",
|
||||||
|
" 'task_name': 'RSS基于规则数据处理',\n",
|
||||||
|
" 'task_id': 2,\n",
|
||||||
|
" 'execution_time': 1.2610254287719727,\n",
|
||||||
|
" 'output': \"RSS数据处理完成！\\n处理统计: {'total_articles': 8, 'filtered_articles': 1, 'filter_rate': 0.125, 'processing_time': '2025-10-23 16:57:21', 'save_success': True, 'mark_success': True}\\n\",\n",
|
||||||
|
" 'error': None}"
|
||||||
|
]
|
||||||
|
},
|
||||||
|
"execution_count": 2,
|
||||||
|
"metadata": {},
|
||||||
|
"output_type": "execute_result"
|
||||||
|
}
|
||||||
|
],
|
||||||
"source": [
|
"source": [
|
||||||
"# 手动执行任务\n",
|
"# 手动执行任务（异步方式，快速返回）\n",
|
||||||
"def run_task_manually(task_id):\n",
|
"def run_task_manually(task_id):\n",
|
||||||
" display(Markdown(f\"### 正在手动执行任务ID {task_id}...\"))\n",
|
" display(Markdown(f\"### 正在手动执行任务ID {task_id}...\"))\n",
|
||||||
" success = manager.run_task_manually(task_id)\n",
|
" success = manager.run_task_manually(task_id)\n",
|
||||||
@@ -720,118 +979,42 @@
|
|||||||
" display(Markdown(f\"### 任务ID {task_id} 执行失败\"))\n",
|
" display(Markdown(f\"### 任务ID {task_id} 执行失败\"))\n",
|
||||||
" return success\n",
|
" return success\n",
|
||||||
"\n",
|
"\n",
|
||||||
"# 执行：手动运行任务ID为1的任务\n",
|
"# 手动执行任务（同步方式，显示详细执行过程）\n",
|
||||||
"run_task_manually(1)"
|
"def run_task_with_details(task_id):\n",
|
||||||
],
|
" display(Markdown(f\"### 开始执行任务ID {task_id}\"))\n",
|
||||||
"outputs": [
|
" display(Markdown(\"---\"))\n",
|
||||||
{
|
" \n",
|
||||||
"data": {
|
" result = manager.run_task_synchronously(task_id)\n",
|
||||||
"text/plain": [
|
" \n",
|
||||||
"<IPython.core.display.Markdown object>"
|
" if not result['success'] and result.get('error') and 'task_id' not in result:\n",
|
||||||
],
|
" display(Markdown(f\"### ❌ 错误: {result['error']}\"))\n",
|
||||||
"text/markdown": "### 正在手动执行任务ID 1..."
|
" return result\n",
|
||||||
},
|
" \n",
|
||||||
"metadata": {},
|
" # 显示任务基本信息\n",
|
||||||
"output_type": "display_data",
|
" display(Markdown(f\"**任务名称**: {result['task_name']}\"))\n",
|
||||||
"jetTransient": {
|
" display(Markdown(f\"**任务ID**: {result['task_id']}\"))\n",
|
||||||
"display_id": null
|
" display(Markdown(f\"**执行时长**: {result['execution_time']:.2f} 秒\"))\n",
|
||||||
}
|
" display(Markdown(\"---\"))\n",
|
||||||
},
|
" \n",
|
||||||
{
|
" # 显示执行输出\n",
|
||||||
"name": "stdout",
|
" if result['output']:\n",
|
||||||
"output_type": "stream",
|
" display(Markdown(\"### 📋 执行输出:\"))\n",
|
||||||
"text": [
|
" print(result['output'])\n",
|
||||||
"\u001B[32m2025-10-17 13:44:35\u001B[0m | \u001B[1mINFO \u001B[0m | \u001B[36mmysql_agent\u001B[0m - \u001B[1m查询执行成功\u001B[0m\n",
|
" display(Markdown(\"---\"))\n",
|
||||||
"\u001B[32m2025-10-17 13:44:35\u001B[0m | \u001B[1mINFO \u001B[0m | \u001B[36mtask_scheduler\u001B[0m - \u001B[1m开始执行任务: RSS新闻订阅\u001B[0m\n"
|
" \n",
|
||||||
]
|
" # 显示执行结果\n",
|
||||||
},
|
" if result['success']:\n",
|
||||||
{
|
" display(Markdown(\"### ✅ 任务执行成功\"))\n",
|
||||||
"data": {
|
" else:\n",
|
||||||
"text/plain": [
|
" display(Markdown(f\"### ❌ 任务执行失败\"))\n",
|
||||||
"<IPython.core.display.Markdown object>"
|
" if result['error']:\n",
|
||||||
],
|
" display(Markdown(f\"**错误信息**: {result['error']}\"))\n",
|
||||||
"text/markdown": "### 任务ID 1 执行成功"
|
" \n",
|
||||||
},
|
" return result\n",
|
||||||
"metadata": {},
|
"\n",
|
||||||
"output_type": "display_data",
|
"# 执行：手动运行任务ID为2的任务（显示详细执行过程）\n",
|
||||||
"jetTransient": {
|
"run_task_with_details(2)"
|
||||||
"display_id": null
|
]
|
||||||
}
|
|
||||||
},
|
|
||||||
{
|
|
||||||
"data": {
|
|
||||||
"text/plain": [
|
|
||||||
"True"
|
|
||||||
]
|
|
||||||
},
|
|
||||||
"execution_count": 5,
|
|
||||||
"metadata": {},
|
|
||||||
"output_type": "execute_result"
|
|
||||||
},
|
|
||||||
{
|
|
||||||
"name": "stdout",
|
|
||||||
"output_type": "stream",
|
|
||||||
"text": [
|
|
||||||
"\u001B[32m2025-10-17 13:44:37\u001B[0m | \u001B[1mINFO \u001B[0m | \u001B[36mrss_subscriptions\u001B[0m - \u001B[1m新闻API客户端初始化完成，已连接到数据库\u001B[0m\n",
|
|
||||||
"\u001B[32m2025-10-17 13:44:37\u001B[0m | \u001B[1mINFO \u001B[0m | \u001B[36mrss_subscriptions\u001B[0m - \u001B[1m数据库表结构验证通过，当前字段：['id', '文章标题', '文章链接', '文章摘要', '发布时间', '来源URL', '创建时间', '更新时间']\u001B[0m\n",
|
|
||||||
"\u001B[32m2025-10-17 13:44:37\u001B[0m | \u001B[1mINFO \u001B[0m | \u001B[36mrss_subscriptions\u001B[0m - \u001B[1m上次更新时间: 2025-10-16 08:11:07\u001B[0m\n",
|
|
||||||
"\u001B[32m2025-10-17 13:44:37\u001B[0m | \u001B[1mINFO \u001B[0m | \u001B[36mrss_subscriptions\u001B[0m - \u001B[1m开始获取RSS源数据...\u001B[0m\n"
|
|
||||||
]
|
|
||||||
},
|
|
||||||
{
|
|
||||||
"name": "stderr",
|
|
||||||
"output_type": "stream",
|
|
||||||
"text": [
|
|
||||||
"D:\\ProgramTools\\anaconda3\\envs\\intelligence_system\\Lib\\site-packages\\requests\\__init__.py:86: RequestsDependencyWarning: Unable to find acceptable character detection dependency (chardet or charset_normalizer).\n",
|
|
||||||
" warnings.warn(\n"
|
|
||||||
]
|
|
||||||
},
|
|
||||||
{
|
|
||||||
"name": "stdout",
|
|
||||||
"output_type": "stream",
|
|
||||||
"text": [
|
|
||||||
"\u001B[32m2025-10-17 13:44:38\u001B[0m | \u001B[1mINFO \u001B[0m | \u001B[36mrss_subscriptions\u001B[0m - \u001B[1mRSS源获取完成，成功获取 4/4 个源\u001B[0m\n",
|
|
||||||
"\u001B[32m2025-10-17 13:44:38\u001B[0m | \u001B[1mINFO \u001B[0m | \u001B[36mrss_subscriptions\u001B[0m - \u001B[1m获取完成，耗时: 0.72秒\u001B[0m\n",
|
|
||||||
"\u001B[32m2025-10-17 13:44:38\u001B[0m | \u001B[1mINFO \u001B[0m | \u001B[36mrss_subscriptions\u001B[0m - \u001B[1m开始处理 RSS 源: https://www.chinanews.com.cn/rss/china.xml\u001B[0m\n",
|
|
||||||
"\u001B[32m2025-10-17 13:44:38\u001B[0m | \u001B[1mINFO \u001B[0m | \u001B[36mmysql_agent\u001B[0m - \u001B[1m表 collector_rss_subscriptions 插入结果汇总\u001B[0m\n",
|
|
||||||
"\u001B[32m2025-10-17 13:44:38\u001B[0m | \u001B[1mINFO \u001B[0m | \u001B[36mrss_subscriptions\u001B[0m - \u001B[1m成功写入 30/30 条记录\u001B[0m\n",
|
|
||||||
"\u001B[32m2025-10-17 13:44:38\u001B[0m | \u001B[1mINFO \u001B[0m | \u001B[36mrss_subscriptions\u001B[0m - \u001B[1m开始处理 RSS 源: https://www.chinanews.com.cn/rss/world.xml\u001B[0m\n",
|
|
||||||
"\u001B[32m2025-10-17 13:44:39\u001B[0m | \u001B[33m\u001B[1mWARNING \u001B[0m | \u001B[36mmysql_agent\u001B[0m - \u001B[33m\u001B[1m表 collector_rss_subscriptions 中跳过重复记录\u001B[0m\n",
|
|
||||||
"\u001B[32m2025-10-17 13:44:39\u001B[0m | \u001B[33m\u001B[1mWARNING \u001B[0m | \u001B[36mmysql_agent\u001B[0m - \u001B[33m\u001B[1m表 collector_rss_subscriptions 中跳过重复记录\u001B[0m\n",
|
|
||||||
"\u001B[32m2025-10-17 13:44:39\u001B[0m | \u001B[1mINFO \u001B[0m | \u001B[36mmysql_agent\u001B[0m - \u001B[1m表 collector_rss_subscriptions 插入结果汇总\u001B[0m\n",
|
|
||||||
"\u001B[32m2025-10-17 13:44:39\u001B[0m | \u001B[31m\u001B[1mERROR \u001B[0m | \u001B[36mmysql_agent\u001B[0m - \u001B[31m\u001B[1m表 collector_rss_subscriptions 插入失败记录详情\u001B[0m\n",
|
|
||||||
"\u001B[32m2025-10-17 13:44:39\u001B[0m | \u001B[1mINFO \u001B[0m | \u001B[36mrss_subscriptions\u001B[0m - \u001B[1m成功写入 28/30 条记录\u001B[0m\n",
|
|
||||||
"\u001B[32m2025-10-17 13:44:39\u001B[0m | \u001B[1mINFO \u001B[0m | \u001B[36mrss_subscriptions\u001B[0m - \u001B[1m开始处理 RSS 源: https://www.chinanews.com.cn/rss/finance.xml\u001B[0m\n",
|
|
||||||
"\u001B[32m2025-10-17 13:44:39\u001B[0m | \u001B[1mINFO \u001B[0m | \u001B[36mmysql_agent\u001B[0m - \u001B[1m表 collector_rss_subscriptions 插入结果汇总\u001B[0m\n",
|
|
||||||
"\u001B[32m2025-10-17 13:44:39\u001B[0m | \u001B[1mINFO \u001B[0m | \u001B[36mrss_subscriptions\u001B[0m - \u001B[1m成功写入 30/30 条记录\u001B[0m\n",
|
|
||||||
"\u001B[32m2025-10-17 13:44:39\u001B[0m | \u001B[1mINFO \u001B[0m | \u001B[36mrss_subscriptions\u001B[0m - \u001B[1m开始处理 RSS 源: https://www.chinanews.com.cn/rss/scroll-news.xml\u001B[0m\n",
|
|
||||||
"\u001B[32m2025-10-17 13:44:39\u001B[0m | \u001B[33m\u001B[1mWARNING \u001B[0m | \u001B[36mmysql_agent\u001B[0m - \u001B[33m\u001B[1m表 collector_rss_subscriptions 中跳过重复记录\u001B[0m\n",
|
|
||||||
"\u001B[32m2025-10-17 13:44:39\u001B[0m | \u001B[33m\u001B[1mWARNING \u001B[0m | \u001B[36mmysql_agent\u001B[0m - \u001B[33m\u001B[1m表 collector_rss_subscriptions 中跳过重复记录\u001B[0m\n",
|
|
||||||
"\u001B[32m2025-10-17 13:44:39\u001B[0m | \u001B[33m\u001B[1mWARNING \u001B[0m | \u001B[36mmysql_agent\u001B[0m - \u001B[33m\u001B[1m表 collector_rss_subscriptions 中跳过重复记录\u001B[0m\n",
|
|
||||||
"\u001B[32m2025-10-17 13:44:39\u001B[0m | \u001B[33m\u001B[1mWARNING \u001B[0m | \u001B[36mmysql_agent\u001B[0m - \u001B[33m\u001B[1m表 collector_rss_subscriptions 中跳过重复记录\u001B[0m\n",
|
|
||||||
"\u001B[32m2025-10-17 13:44:39\u001B[0m | \u001B[33m\u001B[1mWARNING \u001B[0m | \u001B[36mmysql_agent\u001B[0m - \u001B[33m\u001B[1m表 collector_rss_subscriptions 中跳过重复记录\u001B[0m\n",
|
|
||||||
"\u001B[32m2025-10-17 13:44:39\u001B[0m | \u001B[33m\u001B[1mWARNING \u001B[0m | \u001B[36mmysql_agent\u001B[0m - \u001B[33m\u001B[1m表 collector_rss_subscriptions 中跳过重复记录\u001B[0m\n",
|
|
||||||
"\u001B[32m2025-10-17 13:44:39\u001B[0m | \u001B[33m\u001B[1mWARNING \u001B[0m | \u001B[36mmysql_agent\u001B[0m - \u001B[33m\u001B[1m表 collector_rss_subscriptions 中跳过重复记录\u001B[0m\n",
|
|
||||||
"\u001B[32m2025-10-17 13:44:39\u001B[0m | \u001B[33m\u001B[1mWARNING \u001B[0m | \u001B[36mmysql_agent\u001B[0m - \u001B[33m\u001B[1m表 collector_rss_subscriptions 中跳过重复记录\u001B[0m\n",
|
|
||||||
"\u001B[32m2025-10-17 13:44:39\u001B[0m | \u001B[33m\u001B[1mWARNING \u001B[0m | \u001B[36mmysql_agent\u001B[0m - \u001B[33m\u001B[1m表 collector_rss_subscriptions 中跳过重复记录\u001B[0m\n",
|
|
||||||
"\u001B[32m2025-10-17 13:44:39\u001B[0m | \u001B[33m\u001B[1mWARNING \u001B[0m | \u001B[36mmysql_agent\u001B[0m - \u001B[33m\u001B[1m表 collector_rss_subscriptions 中跳过重复记录\u001B[0m\n",
|
|
||||||
"\u001B[32m2025-10-17 13:44:39\u001B[0m | \u001B[33m\u001B[1mWARNING \u001B[0m | \u001B[36mmysql_agent\u001B[0m - \u001B[33m\u001B[1m表 collector_rss_subscriptions 中跳过重复记录\u001B[0m\n",
|
|
||||||
"\u001B[32m2025-10-17 13:44:39\u001B[0m | \u001B[33m\u001B[1mWARNING \u001B[0m | \u001B[36mmysql_agent\u001B[0m - \u001B[33m\u001B[1m表 collector_rss_subscriptions 中跳过重复记录\u001B[0m\n",
|
|
||||||
"\u001B[32m2025-10-17 13:44:39\u001B[0m | \u001B[33m\u001B[1mWARNING \u001B[0m | \u001B[36mmysql_agent\u001B[0m - \u001B[33m\u001B[1m表 collector_rss_subscriptions 中跳过重复记录\u001B[0m\n",
|
|
||||||
"\u001B[32m2025-10-17 13:44:39\u001B[0m | \u001B[33m\u001B[1mWARNING \u001B[0m | \u001B[36mmysql_agent\u001B[0m - \u001B[33m\u001B[1m表 collector_rss_subscriptions 中跳过重复记录\u001B[0m\n",
|
|
||||||
"\u001B[32m2025-10-17 13:44:39\u001B[0m | \u001B[33m\u001B[1mWARNING \u001B[0m | \u001B[36mmysql_agent\u001B[0m - \u001B[33m\u001B[1m表 collector_rss_subscriptions 中跳过重复记录\u001B[0m\n",
|
|
||||||
"\u001B[32m2025-10-17 13:44:39\u001B[0m | \u001B[33m\u001B[1mWARNING \u001B[0m | \u001B[36mmysql_agent\u001B[0m - \u001B[33m\u001B[1m表 collector_rss_subscriptions 中跳过重复记录\u001B[0m\n",
|
|
||||||
"\u001B[32m2025-10-17 13:44:39\u001B[0m | \u001B[33m\u001B[1mWARNING \u001B[0m | \u001B[36mmysql_agent\u001B[0m - \u001B[33m\u001B[1m表 collector_rss_subscriptions 中跳过重复记录\u001B[0m\n",
|
|
||||||
"\u001B[32m2025-10-17 13:44:39\u001B[0m | \u001B[1mINFO \u001B[0m | \u001B[36mmysql_agent\u001B[0m - \u001B[1m表 collector_rss_subscriptions 插入结果汇总\u001B[0m\n",
|
|
||||||
"\u001B[32m2025-10-17 13:44:39\u001B[0m | \u001B[31m\u001B[1mERROR \u001B[0m | \u001B[36mmysql_agent\u001B[0m - \u001B[31m\u001B[1m表 collector_rss_subscriptions 插入失败记录详情\u001B[0m\n",
|
|
||||||
"\u001B[32m2025-10-17 13:44:39\u001B[0m | \u001B[1mINFO \u001B[0m | \u001B[36mrss_subscriptions\u001B[0m - \u001B[1m成功写入 13/30 条记录\u001B[0m\n",
|
|
||||||
"\u001B[32m2025-10-17 13:44:39\u001B[0m | \u001B[1mINFO \u001B[0m | \u001B[36mrss_subscriptions\u001B[0m - \u001B[1m本次最新更新时间: 2025-10-17 05:41:17\u001B[0m\n",
|
|
||||||
"\u001B[32m2025-10-17 13:44:39\u001B[0m | \u001B[1mINFO \u001B[0m | \u001B[36mtask_scheduler\u001B[0m - \u001B[1m任务执行完成，耗时: 1.85秒\u001B[0m\n",
|
|
||||||
"\u001B[32m2025-10-17 13:44:39\u001B[0m | \u001B[1mINFO \u001B[0m | \u001B[36mtask_scheduler\u001B[0m - \u001B[1m任务执行成功: RSS新闻订阅\u001B[0m\n"
|
|
||||||
]
|
|
||||||
}
|
|
||||||
],
|
|
||||||
"execution_count": 5
|
|
||||||
},
|
},
|
||||||
{
|
{
|
||||||
"cell_type": "markdown",
|
"cell_type": "markdown",
|
||||||
|
|||||||
Reference in New Issue
Block a user